Abstract:

Head pose and gesture offer several key conversational grounding cues and are used extensively in face-to-face interaction among people. We investigate how contextural information can improve visual recognition of feedback gestures during interactions with embodied conversational agents. We present a visual recognition model that integrates cues from the spoken dialogue of an embodied agent with direct observation of a user\'s head pose. In preliminary experiments using a discriminative framework, contextual information improved the performance of head nod detection.